Paper: Co-learning of Word Representations and Morpheme Representations

ACL ID C14-1015
Title Co-learning of Word Representations and Morpheme Representations
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

The techniques of using neural networks to learn distributed word representations (i.e., word embeddings) have been used to solve a variety of natural language processing tasks. The re- cently proposed methods, such as CBOW and Skip-gram, have demonstrated their effectiveness in learning word embeddings based on context information such that the obtained word embed- dings can capture both semantic and syntactic relationships between words. However, it is quite challenging to produce high-quality word representations for rare or unknown words due to their insufficient context information. In this paper, we propose to leverage morphological knowledge to address this problem. Particularly, we introduce the morphological knowledge as both ad- ditional input representation and auxiliary supervi...